In a typical process controller, an input representing, for example, a desired process output is compared to the "actual" process output and causes the controller to set various process parameters, such as pump speeds, flow valve settings, etc., to achieve the desired equality. In the design or adaptation of a controller, the output value that satisfies the input preferably occurs well within the control range for the controller. This allows the controller to operate close to its optimum range.
A PID (proportional, integral and derivative) controller is excellent at identifying errors (such as direction and extent) and in resolving these errors with reiterative mathematical analysis. The PID controller is adaptable to any process control application with appropriate proportional, integral and derivative tuning constants because it does not need information of process characteristics for error resolution. However, when the process characteristics change, the tuning constants set at time of commissioning may no longer be optimal, thus requiring the controller to change its operational position along its operating range. It then frequently becomes necessary to change or "retune" the constants.
Adaptable gain and reset features are recent developments with which a PID controller can keep up with process characteristic changes and resolve errors more proficiently.
Function generators or segment characterizers, as they are also called, are used to provide a particular output curve in response to an input. As an example, the function generator can be used in a process control application where the output of the PID controller serves as the direct or indirect input to a function generator The latter then provides an output that is adapted to regulate an element such as a throttle or valve and the like.
For example, a PID controller may provide an output that is a linear function of its input. The output, however, is applied to a flow-regulating element whose actual flow regulation characteristics are a non-linear function of the PID output. The PID controller adapts to the element's characteristic via its error analysis/resolution, but this may force the PID controller to an extreme operating range under some conditions. The insertion of a function generator, therefore, adapts to the non-linear characteristics curve of the element and allows the PID controller to respond only to deviations from that curve.
However, once the function generator has been configured and inserted, the configuration is constant until one elects to intervene and reconfigure the curve. If process and element characteristics change then the PID controller must again be relied upon to resolve errors.
A need for reconfiguration, typically arises near extreme ends of the operational range. For example, initially a 100% PID controller output signal could result in a function generator output of 73% to satisfy the process. If the process changes and an 85% function generator output would be required to satisfy the process, then this signal could not be generated unless the function generator is first re-configured.